Comparison of Time-Varying and Landmark Analysis Methods in Estimating the Association Between Medication Adherence and Outcomes: A Heart Failure Cohort

Xiwen Simon Qin; Matthew W Knuiman; Joseph Hung; Tom Briffa; Tiew-Hwa Katherine Teng; Frank M Sanfilippo

doi:10.23889/ijpds.v5i5.1485

Xiwen Simon Qin

Centre for Medication Use and Safety, Monash University. School of Population and Global Health, The University of Western Australia

Matthew W Knuiman

School of Population and Global Health, The University of Western Australia

Joseph Hung

Medical School, Sir Charles Gairdner Hospital Unit, The University of Western Australia

Tom Briffa

School of Population and Global Health, The University of Western Australia

Tiew-Hwa Katherine Teng

National Heart Research Institute, National Heart Centre Singapore, Singapore

Frank M Sanfilippo

School of Population and Global Health, The University of Western Australia

Abstract

Introduction
Medication adherence is associated with a reduction of adverse outcomes in heart failure (HF). However, this association is complex to estimate accurately because adherence (exposure) can vary during the follow-up period. Adherence can be estimated as a fixed exposure to predict outcomes, and this is known as a landmark analysis. In contrast, adherence can also be estimated as a dynamic exposure which varies over time in the follow-up period. This is known as a time-varying analysis and is expected to be the more precise method.

Objectives and Approach
We compared these two methods in a HF cohort. We identified a population-based cohort of 3619 heart failure patients, aged 65-84 years hospitalised in Western Australia from 2003-2007 and who survived to 1-year post-discharge (landmark date). Adherence to renin-angiotensin system inhibitors (RASI) and β-blockers was calculated using proportion of days covered (PDC) expressed either as a fixed time exposure (in landmark analysis) or a varying exposure (in time-dependent analysis). The latter was updated every 30 days after the landmark date. Cox regression models were used to investigate the association between adherence and all-cause death at 1- and 3-years post-landmark date.

Results
For 1-year outcomes, hazard ratios (HR) for every 10% increase in PDC were similar between models from landmark analyses (RASI adherence: 0.93, 0.90-0.97; β-blocker adherence: 0.96, 0.92-1.0) and time-dependent analyses (RASI adherence: 0.94, 0.91-0.97; β-blockers adherence: 0.95, 0.92 -0.99). However, 95% confidence intervals estimated from time-dependent models were narrower than those from landmark analyses. HRs were slightly closer to the null when estimated from time-dependent models. A similar pattern was seen with 3-year outcomes.

Conclusion / Implications
Time-dependent analysis of adherence-outcome associations results in more precise estimates of hazard ratios. Estimates of HRs from landmark analysis models were similar but usually lower than those from time-dependent models.

How to Cite

Qin, X. S., Knuiman, M. W., Hung, J., Briffa, T., Teng, T.-H. K. and Sanfilippo, F. M. (2020) “Comparison of Time-Varying and Landmark Analysis Methods in Estimating the Association Between Medication Adherence and Outcomes: A Heart Failure Cohort”, International Journal of Population Data Science, 5(5). doi: 10.23889/ijpds.v5i5.1485.